Among the limited supply of organs available for liver transplantation, a wide spectrum of quality exists. Some organs carry higher risks of disease transmission, and others carry higher risks of graft failure ranging from 20% to 40% at 3 years. Each time an organ offer is made, the patient and physician must decide whether to accept this offer, or wait for a better one to come along. Our prior research has demonstrated that these decisions vary widely by transplant center, are inconsistent with the available evidence, and are susceptible to cognitive biases and external forces such as policy changes and competition between centers. This research proposes to improve organ acceptance decisions, as follows. 1) Using data from the Scientific Registry of Transplant Recipients, we will develop and validate a statistical model to predict whether a given patient would be better off accepting a given offer, versus waiting for a better one to come along. 2) Next, we will use this statistical model to creat and pilot test a point-of-care physician decision aid. This tool will be designed for use on a computer, tablet, or smart phone, and will be intended to guide physicians in deciding whether to accept an organ offer on behalf of a patient.